kdb+ is a column-oriented relational database from kx headquartered in Palo Alto, California.KxKDB+ for real time tick data and analytics2016-01-08T17:26:02.371ZI work in the equities area, where we use kdb for most of our real time tick data requirements. Tick data in our case ranges from market data, real time analytics, live PNL and orders data etc.,It is really fast if chosen for the right problem.
Large logic can be shrunk into a tiny snippet.
It provides a column oriented database, where each column in a table is a vector. Thus you can perform very fast analytics using its vector processing power.,It is sometimes painful to accept the fact that KDB+ is not fully multithreaded.
The ability to write shorter code for a complex logic is really good. But it makes it really cryptic. Cryptic codes are very difficult to maintain and extend.
For some small institutions license cost is little high.,8,It perfectly solves most of our real time tick data needs.
Finding good kdb resources is slightly difficult. Also new people trying to learn kdb experience a relatively longer learning curve.,MemSQL and OneTickROHAN MANEkdb+ is always ahead of its time2016-01-05T18:28:31.494ZI've been using kdb+ in the context of storing and generating analytic from large financial data set for over 10 years. IMHO, no other product provides the performance and flexibility remotely close to kdb+. The build-in language q is very terse and expressive. In one of my former jobs, traders were creating new quantitative models almost "in the speed of thoughts" with kdb+. That really gave us the edge of "time to market".,Time series analysis. The built-in vector operations are extremely fast. Also with the q language you can code up any customized analytical ideas quickly.
The database are all file based, very easy to maintain.
Very solid and fast interface to websocket, so you can interface with javascript easily.,The learning curve is a little steep in the beginning.,10,Fast turn around on delivering new ideas and products.,,Oracle Berkeley DB, TIBCO StreamBase, HadoopYe TianFast but hard to implement2015-12-08T19:39:05.523ZWe use kdb to store and analyze real time market data for transaction cost analysis.,Process large amounts of time series data
Perform quick calculations without use of cursor
Use of window joins and as of joins,Hard to read
Hard to find knowledgeable developers
Lack of good IDE,8,Long development time
Long hiring cycle
Hard to error check,,MySQL, NetBeans,8,,time series data analysis
live tick trading
trading analysis,none,trade execution,9,No,Product Reputation,Looked at the availble talent pool,Don't know,1,No,3,No,We have not had a very positive experience with the solutions KX has provided to our issues.,time series calcutions
easily access and manipulate records without a cursor
ability to create functions withing a given query,indexing multiple columns
readability of the language
debugging,No,7Verified UserPowerful language2015-12-14T16:00:25.258Zkdb+ is very useful in the trading world as it allows analysts to look at huge amounts of data quickly and somewhat easily. Speed was a huge factor.,Efficient computing.
Code interpretation is fast.
Designed with finance in mind.,The language is difficult to learn.
Better solutions are needed for breaking loops without resetting servers.
Include basic templates for fields such as finance, medicine, etc.,6,Increases the speed of the research process.
Allows for quick analysis and results.
Rapid implementation of new ideas.,,BizNet Excel SuiteVerified User

I've been using kdb+ in the context of storing and generating analytic from large financial data set for over 10 years. IMHO, no other product provides the performance and flexibility remotely close to kdb+. The build-in language q is very terse and expressive. In one of my former jobs, traders were creating new quantitative models almost "in the speed of thoughts" with kdb+. That really gave us the edge of "time to market".

When you are dealing with large scale time series data, [there are] no better alternatives. I've seen some firms use other so called "big data" alternatives, and claim they can store the data just as efficiently. However, once you want to generate sophisticated analytics from the data, nothing beats kdb+.